Machine Learning and Artificial Intelligence for Polymer Injection Molding Design and Processing

A special issue of Polymers (ISSN 2073-4360). This special issue belongs to the section "Polymer Processing and Engineering".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 244

Special Issue Editors


E-Mail Website
Guest Editor
School of Mechanical and Automotive Engineering, Clemson University, Greenville, SC 29607, USA
Interests: industry 4.0; industrial IoT; SCADA systems; acquisition and analytics of manufacturing data; physics-regulated AI; data-driven modeling; hybrid manufacturing processes; plastics and composites manufacturing; injection molding; sheet metal forming; specialized tooling
Department of Engineering and Design, Western Washington University, Bellingham, WA 98225, USA
Interests: biopolymers; ocean plastics; upcycling & recycling of plastic products; advanced and intelligent polymer processes; sustainable manufacturing
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Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the transformative role of Machine Learning (ML) and Artificial Intelligence (AI) in the domain of Injection Molding Design and Processing. Focused on unraveling the intricate dynamics within this critical manufacturing process, this Special Issue aims to showcase innovative approaches in modeling, simulation, and process control tailored to injection molding applications. Articles solicited for this Special Issue will spotlight the pivotal role of ML and AI in optimizing and advancing both the design and processing aspects of polymer injection molding. Our focus extends to exploring how these technologies influence and refine process control methodologies specific to injection molding. The intersection of AI with injection molding design and processing will be a central theme, reflecting the evolving landscape of advanced polymer production through injection molding. Authors are encouraged to contribute research that not only advances theoretical frameworks but also rigorously validates them against real-world injection molding scenarios.

We hope that this Special Issue will serve as a dedicated platform for sharing groundbreaking developments, fostering collaboration and catalyzing advancements in the field of advanced polymer injection molding design and processing, without explicit mention of keywords in the abstract.

Dr. Davide Masato
Dr. Saeed Farahani
Dr. Peng Gao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Polymers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • polymer injection molding
  • polymer processing
  • machine learning
  • artificial intelligence

Published Papers

This special issue is now open for submission.
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